{"id":"W31258885","doi":"10.1007/978-1-84628-607-0_8","title":"Design of Reverse Logistics Networks for Multiproducts, Multistates, and Multiprocessing Alternatives","year":2007,"lang":"en","type":"book-chapter","venue":"Springer series in advanced manufacturing","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Cannibalization; Spare part; Reverse logistics; Supply chain; Product (mathematics); Redistribution (election); Waste management; Business; Environmental economics; Engineering; Computer science; Manufacturing engineering; Operations management; Industrial organization","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004551852,0.0008439316,0.0006478825,0.0007762685,0.0006240309,0.001593123,0.001509355,0.0009279139,0.008509388],"category_scores_gemma":[0.0008192019,0.0005973558,0.0006999456,0.0005897069,0.000427638,0.001195784,0.000801935,0.0005125439,0.000870581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001047451,"about_ca_system_score_gemma":0.00119301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002353311,"about_ca_topic_score_gemma":0.006467965,"domain_scores_codex":[0.9996879,0.00008612457,0.00001320204,0.0000765031,0.00008935132,0.00004690601],"domain_scores_gemma":[0.9997351,0.00008513998,0.00004817704,0.00002105157,0.00009349558,0.00001701744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007167988,0.00006285605,0.000332801,0.0001858687,0.00003354411,0.000157403,0.00006410287,0.8929014,0.009694398,0.03308557,0.001630213,0.06178002],"study_design_scores_gemma":[0.00002152184,0.0001147775,0.0001272374,0.00003912091,0.0000362064,0.00008626169,0.00005327028,0.974875,0.004071482,0.01396087,0.006598243,0.00001609757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03168447,0.0005676065,0.9276924,0.0002816636,0.00007005927,0.0002124811,0.0001629822,0.0002798915,0.03904846],"genre_scores_gemma":[0.5572829,0.001171076,0.4201583,0.0001348305,0.00004329738,0.0004479619,0.0002754548,0.0001239739,0.02036209],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008509388,"threshold_uncertainty_score":0.02846676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03090528070340453,"score_gpt":0.2500663532686217,"score_spread":0.2191610725652172,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}